The Association Between Resting Functional Connectivity and Creativity

8/16/2019 The Association Between Resting Functional Connectivity and Creativity

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The Association between Resting Functional Connectivity and Creativity

Hikaru Takeuchi1, Yasuyuki Taki2, Hiroshi Hashizume2, Yuko Sassa 2, Tomomi Nagase3, Rui Nouchi1 and Ryuta Kawashima 1,2,4

1Smart Ageing International Research Center, Institute of Development, Aging and Cancer and 2Division of DevelopmentalCognitive Neuroscience, Institute of Development, Aging and Cancer and 3Faculty of Medicine and 4Department of Functional BrainImaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan

Address correspondence to Hikaru Takeuchi, Smart Ageing International Research Center, Institute of Development, Aging and Cancer, TohokuUniversity, 4-1, Seiryo-cho, Aoba-ku, Sendai 980-8575, Japan. Email: [email protected].

The analysis of functional connectivity at rest (rFC) enables us to

know how brain regions within and between networks interact.

In this study, we used resting-state functional magnetic resonance

imaging and a creativity test of divergent thinking (DT) to investi-

gate the relationship between creativity measured by DT and rFC.

We took the medial prefrontal cortex (mPFC) to be the seed region

and investigated correlations across subjects between the score of

the DT test and the strength of rFC between the mPFC and other

brain regions. Our results showed that the strength of rFC with the

mPFC significantly and positively correlated with creativity as

measured by the DT test in the posterior cingulate cortex (PCC).

These results showed that higher creativity measured by DT is

associated with rFC between the mPFC and the PCC, the key nodes

of the default mode network (DMN). Increased rFC between these

regions is completely opposite from that is generally expected from

the association between higher creativity and reduced deactivation

in DMN during an externally directed attention-demanding task

shown in our previous study but is similar to the pattern seen in

relatives of schizophrenia. These findings are comparable to the

previously reported psychological associations between schizotypy

and creativity.

Keywords: creativity, default mode network, functional connectivity,

posterior cingulate cortex, rest

Introduction

Creativity is commonly agreed to involve bringing somethinginto being that is original and also valuable (Ochse 1990). It has been essential to the development of human civilization and

plays a crucial role in cultural life. Creativity has often beenmeasured by divergent thinking (DT) tests psychometrically.DT pertains primarily to information retrieval and the call fora number of varied responses to a certain item (Guilford 1967).

As summarized in Jung, Segall, et al. (2010), there are a number

of cognitive processes that are important for creativity, suchas flow (when a person is fully immersed in what he or sheis doing; characterized by a feeling of energized focus, fullinvolvement, and success in the process of the activity [Csikszentmihalyi 1997]), insight (the flash of recognition that

solves a problem [Jung-Beeman et al. 2004]), perseverance inthe face of social acceptance or resistance, such as that of personality variables, and also remote association of ideas. These and other cognitive processes contribute to the complex

construct of creativity. As DT tests include a wide range of cognitive processes (Dietrich 2007), attempts ought to beundertaken to move beyond a reliance on DT tests to assesscreativity in laboratory settings (Dietrich 2007). However, wefocused on the DT test as a measure of creativity in this study

because, right now, DT tests dominate as a measure of creativity in this field (Dietrich 2007). DT has been proposed to be a key

aspect of creativity (Guilford 1967) and a meta-analysis (Kim

2008) furthermore demonstrated that DT scores have a signif-

icantly stronger relationship with creative achievement than

scores on intelligence tests do supporting the validity of DT as

predictive of creative ability. To our knowledge, no other

creative measures in laboratory settings have shown this levelof validity. The major weak points of DT tests as described

above are actually more or less common to comprehensive psychological tests of these kinds, such as ‘‘intelligence tests,’’

‘‘processing speed tasks,’’ and ‘‘reading comprehension tasks.’’

For example, in the case of the processing speed task, the digit

symbol test (Wechsler 1997), which is a typical test of

processing speed, is considered to be affected by psychomotorspeed, attention, perceptual organization, motor persistence,

and visual short-term memory (Schear and Sato 1989; Ellingsen

et al. 2001). We should remember the weak points of these

psychological tasks, for we believe it would take quite a lot of

time to develop psychological tasks without these limitations.One of the most consistent psychological findings regarding

creativity is creativity’s association with schizotypy and open-

ness, as described below. Numerous studies reported a positive

relationship between creativity and schizotypy (Fisher et al.2004), and a positive relationship between creativity and open-ness (Dollinger et al. 2004; Carson et al. 2005; Miller and Tal

2007). Schizotypy refers to the personality trait of experiencing psychotic symptoms (Claridge 1997), which are also observedin normal populations (Johns and van Os 2001); the continuity of psychotic symptoms with normal experience has also been pointed out (Johns and van Os 2001). Furthermore, schizotypy may be conceptualized as a predisposition to schizophrenia at

the level of personality organization not only among clinical populations but also normal populations (Meehl 1989; Vollema and Van Den Bosch 1995; van’t Wout et al. 2004). Moreover,

the abovementioned association between schizotypy and crea-

tivity as well as the association between creativity and opennessis clearly observed in normal populations (Green and Williams1999; Miller and Tal 2007; Jung, Grazioplene, et al. 2010).Openness is a personality trait that involves an active imagina-tion, daydreaming, aesthetic sensitivity, preference for variety,

and intellectual curiosity (McCrae 1987; Costa and McCrae1992). Recently, Miller and Tal (2007) investigated associationsamong creativity, schizotypy, and openness. Consistent with vast numbers of previous studies, in their sample of college

students, schizotypy correlated with creativity as well as open-ness and openness correlated with creativity. In their study, ina multiple regression model predicting creativity, the partialcontribution of openness was statistically significant, while thatof positive schizotypy was not. Their results may indicate that

The Author 2012. Published by Oxford University Press. All rights reserved.For permissions, please e-mail: [email protected]

doi:10.1093/cercor/bhr371

Advance Access publication January 10, 2011

Cerebral Cortex December 2012;22:2921–2929


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the ‘‘schizotypy--creativity’’ link may be mediated by the per-sonality trait of openness. Their results may suggest a path

model where openness fully mediates the effect of schizotypy on creativity (i.e., schizotypy increases openness which, in turn,augments creativity) (Del Giudice et al. 2010) or 2 constructsmay tap some of the same psychological processes (DelGiudice et al. 2010) that should not be partialled out. In either

case, the natures of the associations among the 3 remain to be

investigated. The strongly consistent findings from thesestudies are that there are associations between creativity andschizotypy as well as between creativity and openness. Other

studies suggest a genetic association between psychosis andcreativity. For example, the first-degree relatives and the off-spring of people with schizophrenia tend to be more creativeand enter more creative occupations than controls (Juda 1949;Karlsson 1970, 1984, 2001). Furthermore, the prevalent geno-type of the neuregulin 1 gene that increases the risk of

psychosis (Hall et al. 2006; Ke ´ri et al. 2009) is associated withincreased creativity (Ke ´ri 2009).

Other cognitive components such as latent inhibition and

deficits of selective attention may be associated with or may

mediate the association between schizotypy and creativity.Latent inhibition is the capacity to screen from consciousawareness stimuli previously experienced as irrelevant. Pre- vious studies revealed evidence that a heightened level of creativity is associated with attenuated latent inhibition (Carsonet al. 2003; Fink, Slamar-Halbedl, et al. 2011), while attenuated

latent inhibition has been generally associated with the tendency toward schizotypy (Carson et al. 2003). Accordingly, creativeindividuals do not tend to screen things out from conscious

awareness that were previously experienced as irrelevant. Thisattenuated latent inhibition is assumed to be associated withselective attention deficits (Lubow 2005), while selectiveattention deficits have also been associated with heightenedcreativity (for summary, see Takeuchi, Taki, Hashizume, et al.

2011c). From these points, it can be said, ‘‘creative individualsappear to be characterized in part by the ability to perceive anddescribe what remains hidden from the view of others’’ (Carsonet al. 2003).

Neuroimaging studies have shown the higher creativity is

associated with brain connectivity and the functions of thefrontal lobe. Schizotypes, who have enhanced creative thinkingability, increasingly recruit the right prefrontal cortex (PFC)during a DT test (Folley and Park 2005). Furthermore, our previous study of regional gray matter structures has shown the

right PFC’s gray matter structure was associated with creativity as measured by DT (Takeuchi, Taki, Hashizume, et al. 2011c).On the other hand, in healthy subjects, a previous electroen-

cephalogram (EEG) study (Jausovec 2000) reported thatcreative individuals showed higher interhemispheric and

intrahemispheric EEG coherence (functional connectivity [FC]) during essay writing. In another EEG study (Jausovec Nand Jausovec K 2000), a creative or divergent production problem (essay writing) caused noticeable intrahemispheric

and interhemispheric cooperation, mainly between the fardistant brain regions, compared with a nondivergent problem. The authors suggested that creative thinking seemed to requireinformation transfer between different brain areas. In addition, when subjects hit upon more original ideas during a creative

task, stronger task-related alpha synchronization was observed(Fink and Neubauer 2006). Furthermore, white matter struc-tural integrity (structural connectivity), involving the corpus

callosum and the frontal lobe, was associated with creativity asmeasured by a DT test (Takeuchi et al. 2010b). These findingsare consistent with integrative reviews that suggest the

importance of brain connectivity for creativity (Heilman et al.2003; Duch 2007; but see also Jung, Grazioplene, et al. 2010 forthe negative association of creativity and the white matterstructural integrity of inferior frontal areas). As a whole, the

results of those studies indicate higher creativity may well be

associated with brain connectivity and the functions of thefrontal lobe. Structural connectivity underlies both FC duringa task (Au Duong et al. 2005) and FC during rest (rFC)(Greicius et al. 2009; Honey et al. 2009). Therefore, considering

the associations between creativity and structural connectivity and those between creativity and FC during a task, it can bereasoned that creativity is related to rFC.

Recently, rFC, which reflects temporal correlations between blood oxygen level--dependent (BOLD) signals in different

brain regions during rest, has been widely used in functionalmagnetic resonance imaging (fMRI) studies. These temporalcorrelations suggest direct or indirect interactions between brain regions (Friston et al. 1993). Certain sets of regions show

positively synchronized brain activity during rest (positivecorrelations between the brain activities of these regions) andform functional networks (Damoiseaux et al. 2006). Oneimportant finding obtained from a study of rFC is that thereare 2 networks, the so called default mode network (DMN) andthe task-positive network (TPN), whose brain activities during

rest show spontaneous correlations within each network andanticorrelations between networks (Fox et al. 2005). Anti-correlations mean that when one network is activated, the

other network is deactivated. The TPN consists of regions thatare consistently activated during cognitive tasks, such as thelateral PFC (LPFC) and the inferior parietal lobe, and the DMNconsists of regions that are consistently deactivated duringcognitive tasks, such as the medial PFC (mPFC) and the pos-

terior cingulate cortex (PCC) (Fox et al. 2005). Higher psy-chometric intelligence is associated with an higher correlation within the TPN (Song et al. 2008). On the other hand, relativesof schizophrenic persons show increased rFC within the DMN(Whitfield-Gabrieli et al. 2009).

In our previous studies, as described above, we investigatedthe characteristics of regional gray matter volume, whitematter structural integrity, and functional activity during a working memory task that are shown by subjects with highercreativity measured by DT (Takeuchi et al. 2010a, 2010b; Takeuchi, Taki, Hashizume, et al. 2011c). Of note, the reduced

task-induced deactivation (TID) in the precuneus, which isone of the key nodes of the DMN was associated with higher

creativity. This was interpreted as reflection of the inefficientreallocation of cognitive resources in the creative subjects

and this finding was also comparable to the finding of thereduced TID in the DMN in relatives of schizophrenic persons(Whitfield-Gabrieli et al. 2009). The interpretation of reduced TID in the DMN in the creative subjects is congruent with theabovementioned previously reported association between

creativity and deficits of selective attention. However, despitethese and a number of neuroimaging studies which investigated the functional activities of the brain during variouscreative tasks (e.g., Cha ́vez-Eakle et al. 2007; Gibson et al.

2009) and the structural characteristics of the brains of creative subjects (Jung et al. 2009; Jung, Grazioplene, et al.2010; Jung, Segall, et al. 2010), including the ones as described

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above (for review, see Arden et al. 2010), the association between rFC and creativity has not been investigated. Using

resting-state fMRI scans of the subjects whose fMRI data during a working memory task were analyzed in our study (Takeuchi, Taki, Hashizume, et al. 2011c), we investigated thecorrelations between creativity measured by a DT test (S-A creativity test) (Society_For_Creative_Minds 1969) and the

strength of rFC between the key node of the frontal lobe (the

frontal lobe is associated with creativity, as described above)of the DMN, the mPFC, and regions elsewhere in the brain. The state of the DMN is of interest in investigating the neural

basis of creativity for 3 reasons. First, the DMN is consideredto be involved in daydreaming and self-reflection (Buckneret al. 2008). Creativity is associated with a personality of openness, which is characterized by much imagination,daydreaming, fantasy, and attentiveness to one’s own feelings(McCrae 1987; Costa and McCrae 1992). Second, some recent

previous studies of functional imaging studies of creativecognition reported that the regions of the DMN could becritically involved in creativity (Fink et al. 2010; Fink,

Koschutnig, et al. 2011). Furthermore, the state of the DMN

has been associated with schizotypy, which is associated withcreativity (Fisher et al. 2004), as described above. Finally, theassociation between the activity of the DMN during rest, which is involved in cognitive processes at rest (Buckner et a l.2008), and creativity is intriguing because during the resting period one temporarily stops focusing on the problem being

tackled. This cessation in focus has been suggested tofacilitate creative insight and problem solving (Wallas 1926;Smith and Blankenship 1991; Ward 2003). Using the analysis

of rFC, we are able 1) to know how brain regions interact withnot only brain regions that are directly connected structurally but also with brain regions that are not structurally connected(the latter of which is impossible through studies on whitematter structural integrity), 2) to investigate the state of the

DMN during the cognitive processes involved at rest, and 3)to obtain new insights into the basis of creativity. Twohypotheses can be formed. One is subjects with highercreativity show decreased rFC within the DMN. This is because patient studies showed diseases or disorders with

reduced TID in the DMN are generally associated withreduced rFC within the DMN (for review, see Broyd et al.2009). And our unpublished study (H Takeuchi, Y Taki,R Nouchi, H Hashizume, Y Sassa, A Sekiguchi, Y Kotozaki,S Nakagawa, T Nagase, CM Miyauchi, R Kawashima, un-

published data) also showed reduced TID in the precuneus/PCC regions is associated with reduced rFC within betweenthe mPFC and these precuneus/PCC regions. As described,

creativity is associated with reduced TID in the DMN inthe precuneus/PCC region. Thus, from this perspective,

higher creativity is expected to be associated with reducedrFC between the mPFC and the precuneus/PCC region. Theother hypothesis expects the opposite result and expects theassociation between higher creativity and increased rFC

between the mPFC and the precuneus/PCC region. Thishypothesis was based on the abovementioned observationthat relatives of schizophrenic persons show increased rFC between the mPFC and the precuneus/PCC despite reduced TID in the DMN, while there is a strongly consistent

association between creativity and schizotypy, as describedabove (note this reasoning is not affected whether creativity--schizotypy association is mediated by openness, diffused

attention, or other possible psychological mechanisms, asindicated above).

Materials and Methods

Subjects

One hundred and fifty-nine healthy right-handed individuals (90 menand 69 women) were participated in this study as part of our ongoing

project to investigate the associations among brain imaging, cognitivefunctions, and aging (Takeuchi et al. 2010a, 2010b; Takeuchi, Taki,Hashizume, et al. 2011c; Takeuchi, Taki, Sassa, et al. 2011a; Taki et al.2010). Data from 63 subjects among these 159 subjects were used inour previous studies to investigate the association between creativity and brain activity during a working memory task (Takeuchi, Taki,Hashizume, et al. 2011c) as well as the association between creativity and cerebral blood flow during rest (Takeuchi, Taki, Hashizume, et al.2011a). Some of the subjects who took part in this study also becamesubjects of our intervention studies (psychological data and imagingdata recorded before the intervention were used in this study)(Takeuchi, Taki, Hashizume, et al. 2011b; Takeuchi, Taki, Sassa, et al.2011b). Psychological tests and MRI scans not described in this study

were performed together with those described in this study. The meanage of subjects was 21.4 years (standard deviation [SD], 1.8). All subjects

were university students or postgraduates. All subjects had normal vision and none had a history of neurological or psychiatric illness.Handedness was evaluated using the Edinburgh Handedness Inventory (Oldfield 1971).

Creativity Assessment

The S-A creativity test (Society_For_Creative_Minds 1969) was used toassess creativity. A detailed discussion of the psychometric propertiesof this instrument and how it was developed is found in the technicalmanual of this test (Society_For_Creative_Minds 1969). The test is usedto evaluate creativity through DT (Society_For_Creative_Minds 1969),and it involves 3 types of tasks. The first task requires subjects togenerate unique ways of using typical objects. The second task requiressubjects to imagine desirable functions in ordinary objects. The thirdtask requires subjects to imagine the consequences of ‘‘unimaginablethings’’ happening. The S-A creativity test provides a total creativity

score, which was used in this study, as well as scores for the followingdimensions of the creative process: 1) Fluency—Fluency is measured

by the number of relevant responses to questions and is related to theability to produce and consider many alternatives. Fluency scores aredetermined by the total number of questions answered after excludinginappropriate responses or responses that are difficult to understand.2) Flexibility—Flexibility is the ability to produce responses froma wide perspective. Flexibility scores are determined by the sum of the(total) number of category types that responses are assigned basedon a criteria table or an almost equivalent judgment. 3) Originality—Originality is the ability to produce ideas that differ from those of others. Originality scoring is based on the sum of idea categories thatare weighted based on a criteria table or an almost equivalent

judgment. 4) Elaboration—Elaboration is the ability to produce detailedideas (Society_For_Creative_Minds 1969). Elaboration scores are de-

termined by the sum of responses that are weighted based on a criteria table or an almost equivalent judgment. These 4 dimensions corre-spond to the same concepts as those of the Torrance tests of creativethinking (TTCT; Torrance 1966). Scoring of the tests was performed by the Tokyo Shinri Corporation. Please refer to our previous studies(Takeuchi et al. 2010a, 2010b) for more extensive details, includingthose on the psychometric properties of this test, sample answers tothe questionnaire, and the manner in which the tests were scored.

The primary analysis was limited to the total creativity score and didnot include the score for each dimension because this score was highly correlated with the total creativity score as well as with each other(all correlations between the scores of any 2 dimensions had simplecorrelation coefficients of >0.56). This is consistent with another groupof rather similar DT tests (Heausler and Thompson 1988), TTCT(Torrance 1966). Heausler and Thompson (1988) concluded thatthe correlations among the subscales in TTCT were so high that

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each subscale could not provide meaningfully different information. Treffinger (1985) warned that independent interpretations of TTCTsubscores should be avoided. Consistent with this notion, a previousstudy (Cha ́vez-Eakle et al. 2007) that investigated the association

between regional cerebral flow (rCBF) and each dimension revealedthat different creativity dimensions correlated with rCBF in similarregions. Thus, we believe that using only the total creativity scoreserves the purpose of this study. However, it is also true that sometimesthe originality dimension of creativity displays psychometric character-

istics distinct from those of other dimensions (Stavridou and Furnham1996; Abraham et al. 2005). We therefore performed additionalmultiple regression analyses for each dimension as placing the scoresfrom all 4 dimensions (which are strongly correlated) in a singlemultiple regression analysis was statistically inappropriate because of the problem of multicollinearity.

Assessment of Psychometric Measures of General Intelligence

Raven’s Advanced Progressive Matrix (RAPM) (Raven 1993) has beenthe psychometric measure shown to be most correlated with generalintelligence, making it the best measure of general intelligence. Weused RAPM to assess intelligence and also to adjust for the effectgeneral intelligence has on rFC. For more details of how RAPM was

performed in our study, see our previous works (Takeuchi et al. 2010a,2010b).

Behavioral Data Analysis

The behavioral data were analyzed using the statistic software SPSS 16.0(SPSS Inc., Chicago, IL). Associations among demographic variables

were analyzed using simple regression analyses. Results with a P


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correlations is a plus or minus in anticorrelated networks does not

affect the current results and subsequent discussions. Correlation maps

were produced by extracting the BOLD time course from a seed region

then computing the correlation coefficient between that time course

and the time course from all other brain voxels. The seed region in this

study was a 6 mm radius sphere centered on a focus. For the current

study, we examined correlations associated with the key node of the

DMN (the mPFC). The peak voxel of the mPFC (x , y , z = –1, 47, –4) was

defined, as was performed in previous literature (Fox et al. 2005). The

seed region included 123 voxels.For the FC analysis, contrast images representing rFC with the mPFC

were estimated for each subject after preprocessing. Data were subjectto a random-effects analysis, which allowed inferences derived fromthis subject sample to be generalized to the population. To study theeffect of individual difference in creativity measured by a DT test onrFC, we entered the first-level contrast images into a second-levelregression analysis.

Group-Level Statistical Analysis

At the group-level analysis, we tested for a relationship betweenindividual creativity measured by a DT test and rFC with the ROI. In the

whole-brain analysis, we used a multiple linear regression analysis tolook for areas where rFC with the ROI was significantly related to

individual creativity as measured by the DT test (total creativity scorefrom the S-A creativity test). The effects of sex, age, and the score of RAPM were included as regressors of no interest. In additional whole-

brain multiple regression analyses, we tested for a relationship betweeneach dimension of creativity (fluency, flexibility, originality, andelaboration) and rFC with mPFC separately. These additional analysesincluded multiple linear regression analyses, which were performed todetermine areas where rFC with ROI (mPFC) was significantly relatedto each dimension of creativity (the score for each dimension in the S-A creativity test). In these 4 additional analyses, each multiple regressionanalysis had 4 covariates (the score for each dimension in the S-A creativity test, age, sex, and the RAPM score). Refer to the Creativity

Assessment of the Materials and Methods for an explanation of why wedid not add the scores for the 4 dimensions in a single multipleregression analysis.

Next, we tested for a relationship between individual general

intelligence measured by the RAPM score and rFC with mPFC todetermine whether the association between creativity and rFC withROI and that between general intelligence and rFC with ROI wereidentical. Whole-brain analysis included multiple linear regressionanalysis, which was performed to determine areas where rFC withmPFC was significantly associated with individual general intelligenceas measured by the RAPM score. The effects of sex, age, and the totalcreativity score from the S-A creativity test were included as regressorsof no interest.

We then tested for a relationship between individual creativity measured by a DT test and rFC with ROI to determine whethercreativity is also associated with rFC in networks other than DMN. Forthis purpose, we investigated the network involving the bilateraldorsolateral prefrontal cortices (DLPFCs) (Fox et al. 2005). In theseanalyses, 2 seed ROIs (the left and right DLPFC) were included, and the

seed regions were constructed in the same manner as in a previousstudy (Song et al. 2008). Subsequent individual- and group-levelanalyses were performed in the same manner as the analysis of rFC

with mPFC.Next, we investigated whether the relationship between rFC with

mPFC and creativity differed between sexes (i.e., whether interaction between sex and creativity affects rFC with mPFC). In whole-brainanalysis, we used voxelwise analysis of covariance (ANCOVA) in whichsex difference was a group factor (using the full factorial option of SPM5). In this analysis, age, the RAPM score, and the total creativity score from the S-A creativity test were covariates. All of these covariates

were modeled so that each covariate’s unique relationship with rFC with mPFC could be observed for each sex (using the interactionsoption in SPM5), which facilitated investigation of any effect of theinteraction between sex and the covariates for rFC with mPFC. Theseeffects were assessed using t -contrasts.

A multiple comparison correction was performed using the voxel-level familywise error (FWE) approach at the whole-brain level.

Results

Behavioral Data

Table 1 shows the average, the SD, and the range of scores from

the S-A creativity test, the RAPM score, and age in our sample.None of the psychological or epidemiological measures (the

RAPM score, sex, and age) correlated significantly with the totalS-A creativity test score.

Correlation of the Strength of rFC with the mPFC and

Creativity across Sexes

We examined areas showing an association between the DTtest (S-A creativity test) score, which reflects creativity, and the

Table 1

Average, SD, and range of scores from the S-A creativity test, Raven’s advanced progressive

matrices score, and age in our sample

Average SD Range

S-A creativity test score 38.8 9.83 7--67Raven’s advanced progress ive matr ices sco re 28.2 3.66 18--36Age 21.4 1.80 18--27

Figure 1. Regions of correlation between the strength of rFC with the mPFC andcreativity test scores (the results are shown with a threshold of P \ 0.005uncorrected for visualization purposes). Regions of correlation are overlaid on a singlesubject T 1 image of SPM5. As seen, creativity was significantly and positivelycorrelated with the strength of rFC between the mPFC and the posterior cingulategyrus. Below is a scatter plot of the relationships involving rFC between the mPFC andthe PCC (0, 68, 12) and creativity test scores.



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strength of rFC with the mPFC. After controlling for the age,sex, and score of RAPM, a multiple regression analysis revealed

that the total score of the S-A creativity test was significantly and positively correlated with the strength of rFC between themPFC and the PCC (x , y , x =0, –68, 12, t = 5.16, P = 0.038corrected for multiple comparisons at voxel-level FWE at the whole-brain level; Fig. 1). There were no regions of significant

negative correlation between the strength of rFC with the

mPFC and the total score of the S-A creativity test.Moreover, we examined areas showing an association

between each dimension of creativity (fluency, flexibility,

originality, and elaboration) and the strength of rFC with mPFC. We performed 4 separate whole-brain multiple regressionanalyses that included the score for each dimension, age, sex,and the RAPM score as covariates. No significant associations were observed in any of these analyses (P > 0.05 corrected formultiple comparisons at voxel-level FWE at the whole-brain

level). Furthermore, in all analyses, similar tendencies for anassociation between each of the dimensions and the strength of rFC between mPFC and PCC were observed (statistical values

and coordinates of the peak voxel in this region from the

4 analyses were as follows: x , y , x = –

2, –

66, 10, t =

3.75 inthe analysis of fluency; x , y , x = 0, –66, 12, t = 4.17 in the analysisof flexibility; x , y , x = 0, –68, 12, t = 4.41 in the analysis of originality; and x , y , x = 0, –68, 12, t = 4.73 in the analysis of elaboration). Given these results, associations between certaindimensions of creativity and rFC with mPFC remain unclear.

Correlation of the Strength of rFC with the mPFC and

General Intelligence

We also tested for a relationship between individual generalintelligence as measured by RAPM and rFC with mPFC todetermine whether the association between creativity and rFC with ROI and that between general intelligence and rFC with

ROI were identical. After controlling for age, sex, and the total

creativity score from the S-A creativity test, multiple regressionanalysis revealed no significant correlations between the RAPM

score and the strength of rFC with mPFC in any of the regions. A tendency toward a positive correlation between the creativity and the magnitude of rFC between mPFC and a region in PCC(x , y , z = –22, –66, 28, t = 3.30, 6 voxels; P


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creativity that indicated the importance of brain connectivity in creativity and revealed further detail about this finding. The

importance of increased FC in creativity has been shown by previous EEG studies (Jausovec 2000; Jausovec N and JausovecK 2000; Fink and Neubauer 2006) as described in detail in theIntroduction. Our white matter structural study of creativity (Takeuchi et al. 2010b) also showed the importance of

structural connectivity for creativity measured by DT. Together

with the view of integrative reviews of creativity (Heilman et al.2003; Duch 2007), these findings have shown the importanceof brain connectivity for creativity. Our findings are consistent

with this view and further revealed how the precise inter-actions between the key nodes of the DMN are associated withcreativity, which has not been revealed by previous studies of brain connectivity, as described above.

Previously reported increased structural connectivity involving the frontal lobe in subjects with higher creativity

measured by DT may underlie increased rFC with the mPFC insubjects with higher creativity measured by DT. Our previousdiffusion tensor imaging study revealed that white matter

structural integrity involving extensive areas of the frontal lobe,

including the white matter regions adjacent to the mPFC, positively correlated with creativity measured by a DT test(Takeuchi et al. 2010b). Furthermore, structural connectivity underlies increased FC between brain regions (Greicius et al.2009), and it has been implicated that higher individual whitematter integrity underlies stronger FC (Au Duong et al. 2005).

Considering these points, the observed increase in rFC with themPFC in subjects with higher creativity as measured by a DTtest may be partly underlain by previously reported increases

in white matter structural integrity in subjects with highercreativity.

There is at least one limitation in this study as was the case with our previous studies (Jung, Segall, et al. 2010; Takeuchiet al. 2010a, 2010b). We used young healthy subjects with a

high level of education. Limited sampling of the full range of intellectual ability is a common hazard when sampling fromcollege cohorts. Whether our findings would also hold acrossthe full range of population samples and normal distributionmust be determined with larger and more representative

samples. Though our interpretations have a certain limitation as was the case in our previous structural studies on creativity (Takeuchi et al. 2010a, 2010b), focusing on highly intelligentsubjects was certainly warranted for the purpose of this study,given the correlation between intelligence and creativity among

subjects with normal and inferior intelligence (Sternberg2005).

In summary, the present results showed that creativity, as

measured by a DT test, is associated with increased rFC between the mPFC and the PCC, which are the key nodes

of the DMN. Traditionally, it has been suggested that brainconnectivity is important for higher creativity and recentstructural studies confirm that idea. Our current finding isconsistent with this view and further revealed the functional

interaction between the nodes of the DMN is associated withcreativity. Also the increased rFC within the DMN is completely opposite from that is generally expected from the association between higher creativity and reduced TID in this region(Takeuchi, Taki, Hashizume, et al. 2011c). This is because

patient studies showed diseases or disorders with reduced TIDin the DMN are generally associated with reduced rFC withinthe DMN (for review, see Broyd et al. 2009). Furthermore, our

unpublished study (H Takeuchi, Y Taki, R Nouchi,H Hashizume, Y Sassa, A Sekiguchi, Y Kotozaki, S Nakagawa, T Nagase, CM Miyauchi, R Kawashima, unpublished data) also

showed reduced TID in the precuneus/PCC regions isassociated with reduced rFC between the mPFC and these precuneus/PCC regions. Finally, subjects with higher workingmemory performance, which have opposing characteristic

with subjects with higher creativity in certain aspects (for

summary, see Takeuchi, Taki, Hashizume, et al. 2011c), show increased rFC within the DMN (Hampson et al. 2006) andincreased TID in the DMN (Sambataro et al. 2010). However, onthe contrary, the combination of increased rFC within DMN

and reduced TID in DMN, which is observed in creativesubjects, is also observed in the relatives of schizophrenia patients (Whitfield-Gabrieli et al. 2009). These findings arecomparable to those of numerous previous studies that haveshown associations between schizotypy and creativity, in-

cluding those observed in normal populations.

Funding

Japan Science and Technology Agency (JST)/Research Instituteof Science and Technology for society, JST/Core research forEvolutional Science and Technology. A Grant-in-Aid for YoungScientists (B) (KAKENHI 23700306) from the Ministry of Education, Culture, Sports, Science, and Technology.

Notes

We thank Y. Yamada for operating the MRI scanner, the participants,the testers for the psychological tests, and all our other colleagues inIDAC, Tohoku University for their support. Conflict of Interest : Nonedeclared.

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The Association Between Resting Functional Connectivity and Creativity